Title :
Classification of Team Behaviors in Sports Video Games
Author :
Thurau, Christian ; Hettenhausen, Thomas ; Bauckhage, Christian
Author_Institution :
Appl. Comput. Sci., Bielefeld Univ.
Abstract :
This paper considers the application of pattern recognition techniques in modern computer games. Towards the problem of realizing more life-like behavior for artificial game characters, we record the network traffic of online multiplayer games. Dealing with a soccer game, we cluster these data and train HMMs in order to achieve fast and robust recognition of behaviors and actions in the virtual game world. Experimental results indicate that pattern recognition and machine learning provide an auspicious avenue towards more convincing artificial characters
Keywords :
computer games; hidden Markov models; learning (artificial intelligence); pattern classification; HMM; artificial game character; behavior action recognition; computer game; data clustering; hidden Markov model; machine learning; network traffic; online multiplayer game; pattern recognition; soccer game; sports video games; team behavior classification; virtual game world; Application software; Computer science; Games; Hidden Markov models; Humans; Laboratories; Pattern recognition; Principal component analysis; Robustness; Telecommunication traffic;
Conference_Titel :
Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
0-7695-2521-0
DOI :
10.1109/ICPR.2006.370
